metadata
base_model: facebook/vit-mae-base
library_name: transformers
pipeline_tag: image-classification
tags:
- probex
- model-j
- weight-space-learning
Model-J: MAE Model (model_idx_0885)
This model is part of the Model-J dataset, introduced in:
Learning on Model Weights using Tree Experts (CVPR 2025) by Eliahu Horwitz*, Bar Cavia*, Jonathan Kahana*, Yedid Hoshen
🌐 Project | 📃 Paper | 💻 GitHub | 🤗 Dataset
Model Details
| Attribute | Value |
|---|---|
| Subset | MAE |
| Split | test |
| Base Model | facebook/vit-mae-base |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 7e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 885 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9279 |
| Val Accuracy | 0.8552 |
| Test Accuracy | 0.8628 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
rose, skyscraper, girl, clock, keyboard, lobster, worm, cockroach, cloud, elephant, boy, tiger, possum, tank, rabbit, mushroom, chimpanzee, maple_tree, trout, television, bus, beetle, can, beaver, poppy, plate, oak_tree, tractor, flatfish, otter, pickup_truck, bee, aquarium_fish, ray, raccoon, apple, house, crocodile, sea, telephone, turtle, road, cup, couch, crab, snake, pine_tree, plain, lamp, mountain